From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 2
In Part 1 of this series, we defined the Retrieval Augmented Generation (RAG) framework to augment large language models (LLMs) ...
Tag: Building
Building Efficient Neural Networks with JAX
Flax is an advanced neural network library built on top of JAX, aimed at giving researchers and developers a flexible, ...
Your Guide to Building Next-Gen Enterprises
Senior leaders, including CXOs, constantly face the challenge of having to quickly make informed decisions that shape the future of ...
Automate Amazon Bedrock Batch Inference – Building a Scalable and Efficient Pipeline
amazon Bedrock is a fully managed service that offers a selection of high-performance foundation models (FM) from leading ai companies ...
How Druva used Amazon Bedrock to address foundation model complexity when building Dru, Druva’s backup AI copilot
This post is co-written with David Gildea and Tom Nijs from Druva. Druva enables cyber, data, and operational resilience for ...
Beyond Compliance: Building Relationships in Education
Key points: Our country is witnessing the dedication of teachers serving in perhaps the most challenging times in history, and ...
Building a Virtual Try-On Chatbot on WhatsApp
In today’s age of rapid technological advancements, virtual try-on chatbot are revolutionizing how users experience shopping by allowing them to ...
Create an AI-powered generative app building assistant using Amazon Bedrock Agents
In this post, we configure an agent that uses amazon Bedrock Agents to act as a software application creation assistant. ...
From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 1
The AWS Generative ai Innovation Center (GenAIIC) is a team of AWS science and strategy experts who have deep knowledge ...
Building Five Machine Learning Models: From Simplicity to Optimization
Build, compare and optimize models.Model selectionNow we move on to the second part of our project in Selection of machine ...
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